CN104093021A - Monitoring video compression method - Google Patents
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Abstract
The invention relates to a monitoring video compression method. The monitoring video compression method comprises the steps that (1) a video sample is collected; (2) an image is divided into image blocks; (3) a coordinate system is built; (4) a difference reference matrix of the image blocks of the sample is calculated; (5) the difference value of the image blocks of the video image at preset time intervals on site is calculated; (6) repeated frames are judged, and the repeated frames are discarded; (7) video compensation and storage are carried out, processed cache videos are eliminated, and the steps (5), (6) and (7) are repeatedly conducted on videos at the next time interval. Compared with the prior art, the monitoring video compression method solves the problem that it wastes time for a user to search for key information through the videos, and enables a large amount of storage space to be saved when video data are stored in monitoring equipment, thereby meeting QoS requirements of the user.
Description
Technical field
The present invention relates to a kind of video information processing method, especially relate to a kind of monitoring video compression method.
Background technology
Due to the further propelling of Digital Life, the fast development of a series of intelligent Application such as Smart Home, smart mobile phone, wisdom community, intelligent video camera head has played very important effect therein.And in modern society; especially the doorway supervision of individual family and community's corridor monitor area etc. have all been installed a large amount of cameras; the thing that can real time monitoring relates to secure context, and these monitoring cameras often can be taken a large amount of useless static scenes for a long time.Compare with common telecine video scene, monitor video scene often has following Some features: background immobilizes, and foreground object is less, scene is relatively stable, rarely have acute variation, frame speed is slower, and monitor video has low frame per second, feature that frame-to-frame correlation is high.Therefore monitor video has larger Information Compression potentiality than general video, yet the camera that most user uses, substantially be all that all images that collect are stored, collected video flowing is not carried out to repetition rate compression and simplification, especially the loss of a large amount of useless scenes is processed.
Prior art exists following mode to improve the compression ratio of video, has:
1) redundancy on removal time and space.This mode can not be removed content redundancy, still has more content redundancy in monitor video.
2) compression of the content based on every frame, adopts less QP value (quasi-peak value) for important frame, and non-important frame is adopted to larger QP value, increasing compression ratio on the basis of the sharpening of realization preservation important frame.This mode Yi Meizhengwei unit, the whole frame of sharpening for the sub-fraction in a frame, compression performance is still not ideal enough.
Chinese patent 200810216851.4 discloses a kind of video-frequency compression method, comprise and first define video to change the scene be less than or equal to threshold value be background, what be greater than is prospect, then background is carried out to high-quality reference frame and carry out encoding and decoding, prospect is carried out to encoding and decoding with common reference frame, this patent is still preserved repeating frame in prospect, causes the video storage amount after compression still very large.
So be badly in need of a kind of monitoring video compression method, effectively solve the repetition rate compression of multitude of video stream and the simplification problem that monitoring camera gathers.
Summary of the invention
Object of the present invention is exactly to provide a kind of monitoring video compression method that effectively solves the multitude of video stream repetition rate compression of monitoring camera collection and simplify problem in order to overcome the defect of above-mentioned prior art existence.
Object of the present invention can be achieved through the following technical solutions:
A monitoring video compression method, comprising:
Step S1: monitoring camera is placed in static situation, gathers video stream data, and intercepting is play one section of stable video stream data as sample, comprises N GOP in this sample, and each GOP comprises 1 I frame;
Step S2: establish each I two field picture and consist of a * b pixel, each pixel all samples luminance signal, every 8 * 8 pixels form 1 picture piece, and the number of luminance signal picture piece is m * n piece, wherein, m=a/8, n=b/8;
Step S3: horizontal direction and vertical direction at each I two field picture are set up rectangular coordinate system O-XY, draw the two-dimensional coordinate (x, y) of each luminance signal picture piece in image, wherein, x ∈ 1,2 ..., m, y ∈ 1,2 ..., n;
Step S4: the luminance signal picture piece of each coordinate of correspondence in N/2 in sample I frame is carried out
inferior compares between two, obtains corresponding difference R-matrix, then gets remaining N/2 I frame and compare test, obtains the extraordinary image number of blocks after each test, finally obtains judging that whether adjacent I frame is the threshold k of repeating frame;
Step S5: be placed in on-the-spot monitoring camera and first deposit the data of Real-time Collection in buffer, then from buffer, take out the video flowing at Preset Time interval, the I frame of marking GOP on time, calculate current time I frame n (t) and the upper picture piece difference value of corresponding each coordinate between I frame n (t-1) constantly, by comparing as piece difference in respective coordinates in these difference value and difference R-matrix, final statistics exceeds the picture number of blocks of R-matrix picture piece difference range again;
Step S6: be designated as N (t) by what exceed R-matrix in n (t) as number of blocks, if N (t)≤K, n (t) is repeating frame, and abandons, otherwise, the GOP at this I frame place retained;
Step S7: the video flowing abandoning after repeating frame is compensated, and store hard disk into, empty the video flowing of processing in buffer simultaneously, then video flowing repeating step S5, S6, S7 to the next time interval.
Described step S4 specifically comprises:
401: from each luminance signal picture piece of I frame, take out the two-dimensional data matrix of 8 * 8, wherein in matrix, 64 data have represented the brightness value of each pixel of original image, and scope is 0～255;
402: matrix is carried out successively to dct transform, heterogeneity quantizes and except 4, obtains the picture piece condensation matrix of coordinate position (x, y), be designated as T
8 * 8(x, y);
403: N/2 I frame wherein carried out at the luminance signal picture piece condensation matrix of coordinate position (x, y)
inferior subtracts each other between two, and obtaining absolute difference is luminance signal picture piece difference value △ T
8 * 8(x, y), adds up the zone of reasonableness of these differences
be abbreviated as Δ T (x, y), on each coordinate, the difference R-matrix of luminance signal picture piece is designated as:
404: according to the method for step 403, with remaining N/2 I frame, carry out respectively
inferior subtracts each other between two, draws
individual matrix of differences, again these matrixes are contrasted with the difference R-matrix in 403, find out the off-limits extraordinary image piece of the picture piece difference number of correspondence position in each matrix of differences, according to the gathering situation of described extraordinary image piece number, determine a rational threshold k, make the extraordinary image piece number of the adjacent I frame of repetition all be less than K.
N in described step S5 (t) with respect to n (t-1) respective coordinates as piece absolute difference, exceed the picture number of blocks of R-matrix relevant position difference range, be that the zone of reasonableness obtaining according to step 403 in S4 is judged.
Between n in described step S5 (t) and n (t-1), each of corresponding each coordinate is respectively the absolute difference after subtracting each other of corresponding picture piece condensation matrix and n (t-1) under n (t) respective coordinates as piece difference value, and each condensation matrix as piece of described n (t) and n (t-1) is by n (t) and n (t-1) image substitution step 401,402 acquisitions.
Compared with prior art, the present invention has the following advantages:
1) the present invention is by carrying out repeating frame and repeating GOP and lose treatment technology to monitoring camera video flowing, the I frame in live video stream is detected, repetition rate judgement, loses and process and loss compensation is processed, only preserve the dynamic video stream of use, effectively solve the repetition rate compression of multitude of video stream and the simplification problem of camera collection.
2) characteristic information of video image when the difference R-matrix of the luminance signal of sample, blue difference signal and red color difference signal picture piece has comprised static scene all sidedly in the present invention, as repeating frame basis for estimation, can effectively filter out the repeating frame of static scene.The present invention looks like piece by pixel in sample video image is divided into, and carries out otherness signature analysis, the difference R-matrix obtaining.
Accompanying drawing explanation
Fig. 1 is flow chart of the present invention.
Embodiment
Below in conjunction with the drawings and specific embodiments, the present invention is described in detail.The present embodiment be take technical solution of the present invention and is implemented as prerequisite, provided detailed execution mode and concrete operating process, but protection scope of the present invention is not limited to following embodiment.
A kind of monitoring video compression method, relate to repeating frame and GOP loss treatment technology in the video flowing based on MPEG-2, by the I frame in live video stream, detected, repetition rate judgement, lost and process and loss compensation is processed, it is all dynamic and useful making the final video stream data information retaining.The present invention adopts the Frame dropping mechanism of live video stream automatically to detect the situation of change of I frame in video flowing, then I frame and GOP without dynamic change are lost automatically.As shown in Figure 1, the method specifically comprises:
In step S1, sample in selecting video capture card: monitoring camera is placed in static situation, gather video stream data, check data acquisition effect simultaneously, when playing process is highly stable, (collection effect is relatively good, when not having in video flowing more obviously to fluctuate interface) starts to intercept video flowing in a period of time as sample.Video stream frame rate in experiment is 36f/s, and by MPEG-2 frame structure, each GOP (Group Of Picture) comprises 12 two field pictures, gathers the video flowing of 10min, i.e. 1800 GOP, and each GOP comprises 1 I frame (intra-coded frame).
In step S2, image is divided into " piece ": the image difference opposite sex main manifestations of interframe is whether the Pixel Information comprising as piece of a same position in image reaches unanimity.If the pixel of all picture pieces is basic identical, wherein a frame is repeating frame; Otherwise two frames are inconsistent, can not frame losing.And the sign of video information is based on pixel in Moving Picture Experts Group-2, and each comprises 8 * 8 pixels as piece, will be decomposed into pixel as piece and go comparison again.
Suppose that each I two field picture consists of 720 * 576 pixels, each pixel all samples luminance signal, and in Moving Picture Experts Group-2 the sign of video information based on pixel, and each comprises 8 * 8 pixels as piece, luminance signal picture piece is 90 * 72=6480 piece, wherein, 720/8=90,576/8=72.
In step S3, in horizontal direction and the vertical direction of each I two field picture, set up rectangular coordinate system O-XY, draw the two-dimensional coordinate (x, y) of each luminance signal picture piece in image, wherein, x ∈ 1,2 ..., 90, y ∈ 1,2 ..., 72.
In step S4, image difference opposite sex signature analysis: the luminance signal picture piece of each coordinate of correspondence in N/2 in sample I frame is carried out
inferior compares between two, obtains corresponding difference R-matrix, then gets remaining N/2 I frame and compare test, obtains the extraordinary image number of blocks after each test, finally obtains judging that whether adjacent I frame is the threshold k of repeating frame, and concrete steps comprise:
401: from each luminance signal picture piece of I frame, take out the two-dimensional data matrix of 8 * 8, wherein in matrix, 64 data have represented the brightness value of each pixel of original image, and scope is 0～255;
402: matrix is carried out successively to dct transform, heterogeneity quantification and removes 4, therefore in real process, need the data volume of comparison to greatly reduce, and the fluctuation of each pixel brightness value of original image is also eliminated, obtain each luminance signal picture piece at preferred coordinates (x, y) condensation matrix, is designated as T
8 * 8(x, y), makes in sample i I frame and j the I frame luminance signal picture piece condensation matrix on coordinate (x, y) be designated as respectively
with
wherein, i ≠ j and i, j ∈ 1,2 ..., 1800;
403: from coordinate (1,1), start, the luminance signal picture piece condensation matrix by front 900 I frames in this position carries out
inferior subtracts each other between two, and its difference takes absolute value, and is designated as luminance signal picture piece difference value △ T
8 * 8(1,1) statistical discrepancy value scope
be abbreviated as Δ T (1,1), then, by same procedure, obtain the difference value scope on each coordinate
be abbreviated as Δ T (x, y), on each coordinate, the difference R-matrix of luminance signal picture piece is designated as:
404: according to the method for step 403, respectively remaining 900 I frame is carried out
inferior comparison, draws
individual difference matrix, and these matrixes are contrasted with R-matrix, find out the off-limits picture piece of correspondence position picture piece difference number in each difference matrix, then determine a threshold k.Off-limits picture piece number of supposing each I frame is T, and when adjacent two frames compare, if T≤K, adjacent I frame is repeating frame.
In step S5, be placed in on-the-spot monitoring camera and first the data of Real-time Collection deposited in to buffer (buffer register), the video flowing that this buffer can prestore 3 hours continuously, then take out the video flowing of 1 hour at every turn, the I frame of marking GOP, calculates current time I frame n (t) and upper constantly between I frame n (t-1) on time.
N (t) and nt-1) between each of corresponding each coordinate as piece difference value, be respectively after subtracting each other of corresponding picture piece condensation matrix and n (t-1) under n (t) respective coordinates, take absolute value, and these absolute values are formed to a matrix, again with R-matrix comparison, find out the not picture piece number within the scope of R-matrix picture piece absolute difference, and each condensation matrix as piece of n (t) and n (t-1) is by n (t) and n (t-1) image substitution step 401, 402 can obtain, wherein when data are carried out the quantification of DCT system, need carry out Bit-Rate Control Algorithm and quantization scale controls, coding adopts variable-length form.
In step S6, live video stream is carried out to repeating frame and the processing of GOP loss: by what exceed R-matrix in n (t), as piece number scale, be N (t), if N (t)≤K, n (t) is repeating frame, and abandon, otherwise, retain the GOP at this I frame place.
In step S7, the video flowing abandoning after repeating frame is compensated, make it again to become the more smooth video flowing of broadcasting, and store hard disk into the output of fixed bit stream, empty 1 hour video flowing processing in buffer simultaneously, then to lower 1 hour video flowing repeating step S5, S6, S7.
The present invention adopts the Frame dropping mechanism of live video stream, automatically detect the situation of change of I frame in video flowing, again I frame and GOP without dynamic change are lost automatically, it is all dynamic and useful making the final video stream data information retaining, and is particularly suitable for the video stream compression that the camera in the places such as individual digital family, community corridor Kou He factory gathers and processes.
Claims (4)
1. a monitoring video compression method, is characterized in that, comprising:
Step S1: monitoring camera is placed in static situation, gathers video stream data, and intercepting is play one section of stable video stream data as sample, comprises N GOP in this sample, and each GOP comprises 1 I frame;
Step S2: establish each I two field picture and consist of a * b pixel, each pixel all samples luminance signal, every 8 * 8 pixels form 1 picture piece, and the number of luminance signal picture piece is m * n piece, wherein, m=a/8, n=b/8;
Step S3: horizontal direction and vertical direction at each I two field picture are set up rectangular coordinate system O-XY, draw the two-dimensional coordinate (x, y) of each luminance signal picture piece in image, wherein, x ∈ 1,2 ..., m, y ∈ 1,2 ..., n;
Step S4: the luminance signal picture piece of each coordinate of correspondence in N/2 in sample I frame is carried out
inferior compares between two, obtains corresponding difference R-matrix, then gets remaining N/2 I frame and compare test, obtains the extraordinary image number of blocks after each test, finally obtains judging that whether adjacent I frame is the threshold k of repeating frame;
Step S5: be placed in on-the-spot monitoring camera and first deposit the data of Real-time Collection in buffer, then from buffer, take out the video flowing at Preset Time interval, the I frame of marking GOP on time, calculate current time I frame n (t) and the upper picture piece difference value of corresponding each coordinate between I frame n (t-1) constantly, by comparing as piece difference in respective coordinates in these difference value and difference R-matrix, final statistics exceeds the picture number of blocks of R-matrix picture piece difference range again;
Step S6: be designated as N (t) by what exceed R-matrix in n (t) as number of blocks, if N (t)≤K, n (t) is repeating frame, and abandons, otherwise, the GOP at this I frame place retained;
Step S7: the video flowing abandoning after repeating frame is compensated, and store hard disk into, empty the video flowing of processing in buffer simultaneously, then video flowing repeating step S5, S6, S7 to the next time interval.
2. a kind of monitoring video compression method according to claim 1, is characterized in that, described step S4 specifically comprises:
401: from each luminance signal picture piece of I frame, take out the two-dimensional data matrix of 8 * 8, wherein in matrix, 64 data have represented the brightness value of each pixel of original image, and scope is 0～255;
402: matrix is carried out successively to dct transform, heterogeneity quantizes and except 4, obtains the picture piece condensation matrix of coordinate position (x, y), be designated as T
8 * 8(x, y);
403: N/2 I frame wherein carried out at the luminance signal picture piece condensation matrix of coordinate position (x, y)
inferior subtracts each other between two, and obtaining absolute difference is luminance signal picture piece difference value △ T
8 * 8(x, y), adds up the zone of reasonableness of these differences
be abbreviated as Δ T (x, y), on each coordinate, the difference R-matrix of luminance signal picture piece is designated as:
404: according to the method for step 403, with remaining N/2 I frame, carry out respectively
inferior subtracts each other between two, draws
individual matrix of differences, again these matrixes are contrasted with the difference R-matrix in 403, find out the off-limits extraordinary image piece of the picture piece difference number of correspondence position in each matrix of differences, according to the gathering situation of described extraordinary image piece number, determine a rational threshold k, make the extraordinary image piece number of the adjacent I frame of repetition all be less than K.
3. a kind of monitoring video compression method according to claim 2, it is characterized in that, n in described step S5 (t) with respect to n (t-1) respective coordinates as piece absolute difference, exceed the picture number of blocks of R-matrix relevant position difference range, be that the zone of reasonableness obtaining according to step 403 in S4 is judged.
4. a kind of monitoring video compression method according to claim 2, it is characterized in that, between n in described step S5 (t) and n (t-1), each of corresponding each coordinate is respectively the absolute difference after subtracting each other of corresponding picture piece condensation matrix and n (t-1) under n (t) respective coordinates as piece difference value, and each condensation matrix as piece of described n (t) and n (t-1) is by n (t) and n (t-1) image substitution step 401,402 acquisitions.
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| CN105933633A (en) * | 2016-05-20 | 2016-09-07 | 深圳市大拿科技有限公司 | Cloud storage method for content optimization of cloud video |
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| CN113507636A (en) * | 2021-06-30 | 2021-10-15 | 中标慧安信息技术股份有限公司 | Data transmission control method and device between video end and storage end in Internet of things |
| CN115171328A (en) * | 2022-06-30 | 2022-10-11 | 国网北京市电力公司 | Firework identification method, device, equipment and medium based on video compression coding |
| CN115171328B (en) * | 2022-06-30 | 2023-11-10 | 国网北京市电力公司 | Smoke and fire identification method, device, equipment and medium based on video compression coding |
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